activity
20152023
most citedLasHeR: A Large-scale High-diversity Benchmark for RGBT Tracking

300 citations · 1.3k across the 36 of their papers we have counts for

collaborators

36 papers

cs.CV2023

SequencePAR: Understanding Pedestrian Attributes via A Sequence Generation Paradigm

Jiandong Jin, Xiao Wang, Yin Lin +4

Current pedestrian attribute recognition (PAR) algorithms use multi-label or multi-task learning frameworks with specific classification heads. These models often struggle with imb…

cs.CV2023

Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark

Andong Lu, Zhang Zhang, Yan Huang +4

Nighttime person Re-ID (person re-identification in the nighttime) is a very important and challenging task for visual surveillance but it has not been thoroughly investigated. Und…

cs.CV2023

Multi-query Vehicle Re-identification: Viewpoint-conditioned Network, Unified Dataset and New Metric

Aihua Zheng, Chaobin Zhang, Weijun Zhang +4

Existing vehicle re-identification methods mainly rely on the single query, which has limited information for vehicle representation and thus significantly hinders the performance…

cs.CV2023★ 1 cited

Dynamic Enhancement Network for Partial Multi-modality Person Re-identification

Aihua Zheng, Ziling He, Zi Wang +2

Many existing multi-modality studies are based on the assumption of modality integrity. However, the problem of missing arbitrary modalities is very common in real life, and this p…

cs.CV2023

Flare-Aware Cross-modal Enhancement Network for Multi-spectral Vehicle Re-identification

Aihua Zheng, Zhiqi Ma, Zi Wang +1

Multi-spectral vehicle re-identification aims to address the challenge of identifying vehicles in complex lighting conditions by incorporating complementary visible and infrared in…

cs.CV2023★ 1 cited

RGBT Tracking via Progressive Fusion Transformer with Dynamically Guided Learning

Yabin Zhu, Chenglong Li, Xiao Wang +2

Existing Transformer-based RGBT tracking methods either use cross-attention to fuse the two modalities, or use self-attention and cross-attention to model both modality-specific an…